Gaurav Verma

CS Ph.D. Candidate at Georgia Tech
Email: gverma@gatech.edu


[ 📄 curriculum vitae (pdf) ]


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Recent updates
May, 2024 | Two papers will appear at ACL 2024 (Main), covering work on investigating the role of cross-modal projection in multimodal LLMs [preprint] and developing community-centric AI approaches for advancing online safety [coming soon]. One paper on benchmarking of multimodal LLMs [preprint], led by Yiqiao Jin, will appear in Findings of ACL 2024.
May, 2024 | Post a successful thesis proposal, I am a PhD candidate now! 😁
Feb, 2024 | Policy + AI work on using LLMs for large-scale analysis of societal impacts of AI innovation is published in Quantitative Science Studies (QSS)! [pdf, code]
Jan, 2024 | Work on cross-lingual evaluation of LLMs for healthcare queries, co-led by Yiqiao Jin and Mohit Chandra, will appear at WebConf 2024! [pdf, webpage, code]
October, 2023 | Work on modeling text visualness using large vision-language models will appear at EMNLP 2023! [pdf, webpage]
July, 2023 | Honored to be awarded the JPMorgan Chase AI Research Fellowship (2023)! [link]
May, 2023 | Excited to start as a Research Intern with Microsoft Research (FATE) in Montreal! 🍁
May, 2023 | Two papers accepted at ACL 2023 (Main and Findings), covering robustness of multimodal learning [pdf] and adversarial robustness of few-shot learning in NLP [pdf]!
Dec, 2022 | Glad to be one of the recipients of 2022 Snap Research Fellowship 👻! [link]
Nov, 2022 | Passed my Ph.D. Qualifiers at Georgia Tech; here are my slides on Robust Machine Learning for Enabling a Safe, Equitable, and Healthy Web! [slides (pdf)]
Oct, 2022 | Our work on assessing the robustness of multimodal classifiers to text dilutions has been accepted to EMNLP 2022 as a long paper! [pdf] [webpage] [arXiv] [code] [slides (pdf)]
Aug, 2022 | Wrapped up my research internship with Dr. Ani Nenkova and Dr. Ryan A. Rossi at Adobe Research. I had a wonderful time working on understanding image-text interactions!
July, 2022 | Work led by Yunhao Yuan @ Aalto University has been accepted to ICWSM 2023. We study the impact of the pandemic on online LGBTQ+ communities. [pdf]
May, 2022 | Our work on examining the causal relationship between sharing misinformation and experiencing exacerbated anxiety is out in Scientific Reports. Check out the paper here: https://www.nature.com/articles/s41598-022-11488-y.
Mar, 2022 | Our work on using multimodal learning to overcome the language disparity in online content classification has been accepted to ICWSM 2022 🎉 ! [webpage] [pdf]
Jan, 2022 | Happy to share that our work on online ban evasion has been accepted to The Web Conference 2022 🎉 ! [pdf] [dataset]
Oct, 2021 | My collaborators from Adobe Research and I received the Best Paper Runner-up Award 💐 at WISE 2021 for our work on detecting document versions [pdf, image]
June, 2021 | I was one of the winners of ICWSM-2021 Best Reviewer Award 💐
Dec, 2020 | Our work on consuming linear media (like videos) in a non-linear fashion using multimodal fragments has been accepted at IUI 2021! [pdf] [video]
Sep, 2020 | EMNLP 2020: Check out our Findings paper on using reinforcement learning for generating stylized text [arXiv] and our system description for Task 2 at W-NUT [arXiv].
July, 2020 | TechCrunch talks about #ProjectSnippets in their blog! Read it here. This tool is based on our IUI'20 paper on Generating Need Adapted Multimodal Fragments [pdf].
June, 2020 | We participated in ICWSM'20 Safety Data Challenge. Here's our paper.
Mar, 2020 | Check out our work on generating multimodal fragments being presented at this year's Adobe Summit: YouTube video! Here's what the community thinks about #ProjectSnippets! [News]
Feb, 2020 | Our exploration on estimating the causal impact of stylistic attributes on a targeted goal has been accepted at WWW 2020 as a poster! Here's the paper.
Dec, 2019 | Our work on "Generating Need-Adapted Multimodal Fragments" has been accepted at IUI 2020! Check out the paper.
Dec, 2019 | Our work on "Using Image Captions and Multitask Learning for Recommending Query Reformulations" has been accepted at ECIR 2020. Here's the paper on arXiv.
Nov, 2019 | Our work on "Adapting Language Models for Non-Parallel Author-Stylized Rewriting" has been accepted as a full paper at AAAI 2020. Here's the paper on arXiv.
Aug, 2019 | Adobe asked me a few questions on completing one year at Adobe Research [AdobeLife]
Mar, 2019 | Work on command recommendation accepted at UMAP 2019 [project page]
Feb, 2019 | Work on multimodal affective correspondence accepted at ICASSP 2019 [page]

I am a fourth-year Ph.D. candidate in Computer Science at Georgia Tech. My research focuses on robust and efficient vision-language learning , while addressing problems that impact safety , equity , and well-being . I am advised by Prof. Srijan Kumar.

AI for advancing online safety (selected works)
[ACL'24] Community-centric approaches against violence-provoking speech
[WebConf'22] Characterizing, detecting, and predicting online ban evasion
Language equity in AI applications (selected works)
[WebConf'24] LLMs struggle to answer questions in widely spoken languages
[ICWSM'22] Performance disparity in language models across languages

My research interests include: large {vision-language/language} models, multimodal deep learning, natural language processing, and computational social science. At Georgia Tech, I also collaborate closely with Prof. Munmun De Choudhury. I am honored to be supported by the JP Morgan AI PhD Fellowship and Snap Research Fellowship. Here's my [ 📄 CV (pdf)]

Prior to Georgia Tech, I worked at Adobe Research, where I contributed to content generation technologies like #ProjectSnippets. During my doctoral studies, I have been a Research Intern at Microsoft Research and Adobe Research. I completed my undergraduate studies at the Indian Institute of Technology Kanpur, where I worked with Prof. Tanaya Guha on learning modality-independent representations for affective analysis and retrieval of multimedia.

Outside of Computer Science, I also collaborate with Public Policy scholars to study the influence of AI technologies on Public Values and leveraging Generative AI to accelerate Science, Technology, and Policy research.

Recent awards and honors:
JP Morgan AI Research Ph.D. Fellow (2023)
Snap Research Fellow 👻 (2022)
College of Computing Rising Star Doctoral Student Research Award (2022)
• Adobe Research Ph.D. Fellowship Finalist (2022)
• Work covered in TechCrunch, Forbes, Scientific American, The World, ...
• AAAI ICWSM-2021 Best Reviewer Award
• Best Paper Runner-up Award at WISE 2021

Academic Service: Program Committee Member/Reviewer for:
Journals: ACM Transactions on Computer-Human Interaction (TOCHI), IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Data Mining and Knowledge Discovery
Conferences: COLM 2024, AAAI (2022, 2023, 2024), FAccT 2024, ACL 2023, NeurIPS (2023: Ethics reviewer), CHI 2023 (💐 Special Recognition for Outstanding Reviews), KDD 2023, TheWebConf (2022, 2023, 2024), ACL Rolling Review, EMNLP (2021, 2022, 2023), ACL-IJCNLP 2021, ICWSM (2021: 💐 Best Reviewer Award, 2022), ACII 2021, CODS-COMAD 2022, and ECIR 2020.

Apart from research, I enjoy spending most of my time reading books (📚). I also have some affinity for sports – basketball (🏀) and table tennis (🏓). The quickest way to get in touch would be through email (📧). I am also somewhat active on Twitter. More details are available in the Contact section.